Probability for Machine Learning

Probability for Machine Learning
Author :
Publisher : Machine Learning Mastery
Total Pages : 319
Release :
ISBN-10 :
ISBN-13 :
Rating : 4/5 ( Downloads)

Book Synopsis Probability for Machine Learning by : Jason Brownlee

Download or read book Probability for Machine Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-09-24 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability is the bedrock of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in probability that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of probability to machine learning, Bayesian probability, entropy, density estimation, maximum likelihood, and much more.


Probability for Machine Learning Related Books

Probability for Machine Learning
Language: en
Pages: 319
Authors: Jason Brownlee
Categories: Computers
Type: BOOK - Published: 2019-09-24 - Publisher: Machine Learning Mastery

GET EBOOK

Probability is the bedrock of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equation
Multivariate Kernel Smoothing and Its Applications
Language: en
Pages: 249
Authors: José E. Chacón
Categories: Mathematics
Type: BOOK - Published: 2018-05-08 - Publisher: CRC Press

GET EBOOK

Kernel smoothing has greatly evolved since its inception to become an essential methodology in the data science tool kit for the 21st century. Its widespread ad
Nonparametric Econometrics
Language: en
Pages: 768
Authors: Qi Li
Categories: Business & Economics
Type: BOOK - Published: 2023-07-18 - Publisher: Princeton University Press

GET EBOOK

A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametr
Nonparametric Density Estimation
Language: en
Pages: 376
Authors: Luc Devroye
Categories: Mathematics
Type: BOOK - Published: 1985-01-18 - Publisher: New York ; Toronto : Wiley

GET EBOOK

This book gives a rigorous, systematic treatment of density estimates, their construction, use and analysis with full proofs. It develops L1 theory, rather than
Nonparametric Kernel Density Estimation and Its Computational Aspects
Language: en
Pages: 197
Authors: Artur Gramacki
Categories: Technology & Engineering
Type: BOOK - Published: 2017-12-21 - Publisher: Springer

GET EBOOK

This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A